def test_deAlm_analytical_imposed_dt_short():
grid = RasterModelGrid((32, 240), xy_spacing=25)
grid.add_zeros("surface_water__depth", at="node")
grid.add_zeros("topographic__elevation", at="node")
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = _left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500.0:
grid.at_link["surface_water__discharge"][
left_inactive_ids] = grid.at_link["surface_water__discharge"][
left_inactive_ids + 1]
dt = 10.0
deAlm.overland_flow(dt)
h_boundary = ((7.0 / 3.0) * (0.01**2) * (0.4**3) * time)**(3.0 / 7.0)
grid.at_node["surface_water__depth"][grid.nodes[1:-1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = -(7.0 / 3.0) * (0.01**2) * (0.4**2) * (x - (0.4 * 500))
h_analytical[np.where(h_analytical > 0)] = h_analytical[np.where(
h_analytical > 0)]**(3.0 / 7.0)
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def run_day(mg, precipitation: float, duration=1800):
"""
Calculates the mm of water that has infiltrated into soil after a rainfall event.
Rainfall events are assumed to be instantaneous and constant over the model grid.
:param dem: model grid
:param precipitation: rainfall in mm/hr
:param duration: seconds of rainfall
:return: mm of water infiltrated into the soil at every coordinate in the grid
"""
elapsed_time = 0.0
swd = mg.add_zeros('surface_water__depth', at='node', clobber=True)
swd += precipitation
swid = mg.add_zeros('soil_water_infiltration__depth',
at='node',
clobber=True)
swid += 1e-6
siga = SoilInfiltrationGreenAmpt(mg)
of = OverlandFlow(mg, steep_slopes=True)
while elapsed_time < duration:
dt = of.calc_time_step()
dt = dt if dt + elapsed_time < duration else duration - elapsed_time
of.run_one_step(dt=dt)
siga.run_one_step(dt=dt)
elapsed_time += dt
return xr.DataArray(mg.at_node['soil_water_infiltration__depth'].reshape(
mg.shape),
dims=('x', 'y'))
def test_deAlm_analytical():
from landlab import RasterModelGrid
grid = RasterModelGrid((32, 240), spacing = 25)
grid.add_zeros('node', 'surface_water__depth')
grid.add_zeros('node', 'topographic__elevation')
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500.:
grid['link']['surface_water__discharge'][left_inactive_ids] = (
grid['link']['surface_water__discharge'][left_inactive_ids + 1])
dt = deAlm.calc_time_step()
deAlm.overland_flow(dt)
h_boundary = (((7./3.) * (0.01**2) * (0.4**3) *
time) ** (3./7.))
grid.at_node['surface_water__depth'][grid.nodes[1: -1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = (-(7./3.) * (0.01**2) * (0.4**2) * (x - (0.4 * 500)))
h_analytical[np.where(h_analytical > 0)] = (h_analytical[np.where(
h_analytical > 0)] ** (3./7.))
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical():
from landlab import RasterModelGrid
grid = RasterModelGrid((32, 240), spacing=25)
grid.add_zeros('node', 'water__depth')
grid.add_zeros('node', 'topographic__elevation')
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500:
grid['link']['water__discharge'][left_inactive_ids] = (
grid['link']['water__discharge'][left_inactive_ids + 1])
dt = deAlm.calc_time_step()
deAlm.overland_flow(dt)
h_boundary = (((7. / 3.) * (0.01**2) * (0.4**3) * time)**(3. / 7.))
grid.at_node['water__depth'][grid.nodes[1:-1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = (-(7. / 3.) * (0.01**2) * (0.4**2) * (x - (0.4 * 500)))
h_analytical[np.where(h_analytical > 0)] = (h_analytical[np.where(
h_analytical > 0)]**(3. / 7.))
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical_imposed_dt_short():
grid = RasterModelGrid((32, 240), xy_spacing=25)
grid.add_zeros("node", "surface_water__depth")
grid.add_zeros("node", "topographic__elevation")
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500.0:
grid.at_link["surface_water__discharge"][left_inactive_ids] = grid.at_link[
"surface_water__discharge"
][left_inactive_ids + 1]
dt = 10.0
deAlm.overland_flow(dt)
h_boundary = ((7.0 / 3.0) * (0.01 ** 2) * (0.4 ** 3) * time) ** (3.0 / 7.0)
grid.at_node["surface_water__depth"][grid.nodes[1:-1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = -(7.0 / 3.0) * (0.01 ** 2) * (0.4 ** 2) * (x - (0.4 * 500))
h_analytical[np.where(h_analytical > 0)] = h_analytical[
np.where(h_analytical > 0)
] ** (3.0 / 7.0)
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def setup_grid():
from landlab import RasterModelGrid
grid = RasterModelGrid((32, 240), spacing=25)
grid.add_zeros('node', 'water__depth')
grid.add_zeros('node', 'topographic__elevation')
grid.add_zeros('water__discharge', at='active_link')
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
globals().update({'deAlm': OverlandFlow(grid)})
def deAlm():
grid = RasterModelGrid((32, 240), xy_spacing=25)
grid.add_zeros("surface_water__depth", at="node")
grid.add_zeros("topographic__elevation", at="node")
grid.add_zeros("surface_water__discharge", at="link")
return OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
hydrograph_time_hrs = []
# Setting initial fields...
rmg["node"]["topographic__elevation"] = z
rmg["link"]["surface_water__discharge"] = np.zeros(rmg.number_of_links)
rmg["node"]["surface_water__depth"] = np.zeros(rmg.number_of_nodes)
# and fixed link boundary conditions...
rmg.set_fixed_link_boundaries_at_grid_edges(
True, True, True, True, fixed_link_value_of="surface_water__discharge")
# Setting the outlet node to OPEN_BOUNDARY
rmg.status_at_node[100] = 1
# Initialize the OverlandFlow() class.
of = OverlandFlow(rmg, use_fixed_links=True, steep_slopes=True)
# Record the start time so we know how long it runs.
start_time = time.time()
# Link to sample at the outlet
link_to_sample = 299
# Storm duration in seconds
storm_duration = 7200.0
# Running the overland flow component.
while elapsed_time < model_run_time:
# The storm starts when the model starts. While the elapsed time is less
# than the storm duration, we add water to the system as rainfall.
infBandWidthNorm = 0.5
infBandWidth = length * dx / 2 * infBandWidthNorm
channel_left = (length * dx + channel_width) / 2
channel_right = (length * dx - channel_width) / 2
isChannel = np.logical_and(rmg.x_of_node < channel_left,
rmg.x_of_node > channel_right)
highInfBand = np.logical_and(rmg.x_of_node < channel_left + infBandWidth,
rmg.x_of_node > channel_right - infBandWidth)
inf_mask = np.logical_xor(highInfBand, isChannel)
hc[inf_mask] *= 10
of = OverlandFlow(rmg, steep_slopes=True)
SI = SoilInfiltrationGreenAmpt(rmg, hydraulic_conductivity=hc)
elapsed_time = 0
run_time = 1e4
iters = 0
while elapsed_time < run_time:
# First, we calculate our time step.
dt = of.calc_time_step()
# Now, we can generate overland flow.
of.overland_flow()
SI.run_one_step(dt)
# Increased elapsed time
if iters % 1000 == 0:
rmg.set_closed_boundaries_at_grid_edges(True, True, True, True)
# Create fields in the grid for topographic elevation, water depth, discharge.
rmg.add_zeros('topographic__elevation', at='node') # topographic elevation (m)
rmg.add_zeros('water__depth', at='node') # water depth (m)
rmg.add_zeros('water__discharge', at='link') # unit discharge (m2/s)
# Add our initial thin layer of water to the field of water depth.
#rmg['node']['water_depth'] += h_init
# Now we'll identify our leftmost, but interior, column and the IDs of those
# nodes. One column in to prevent issues with BC.
inside_left_edge = rmg.nodes[1:-1, 1]
# Initializing our class...
of = OverlandFlow(rmg, mannings_n=n, theta=0.8, h_init=0.001)
# Now, we need to set a fixed value on the left edge, so we find the
# link neighbor arrays...
of.set_up_neighbor_arrays()
# ... and get a list of all horizonal ids, not just active ids (which is what
# the deAlmeida solution uses)
all_horizontal_ids = links.horizontal_link_ids(rmg.shape)
# from there, we are going to reset our west neighbor array...
of.west_neighbors = (links.horizontal_west_link_neighbor(
rmg.shape, all_horizontal_ids))
# and find the ids of the arrays along the west edge of the grid. We actually
# will set the discharge values here at every time step in the loop.
def deAlm():
grid = RasterModelGrid((32, 240), spacing=25)
grid.add_zeros('surface_water__depth', at='node')
grid.add_zeros('topographic__elevation', at='node')
grid.add_zeros('surface_water__discharge', at='link')
return OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
rmg.set_closed_boundaries_at_grid_edges(True, True, True, True)
# Create fields in the grid for topographic elevation, water depth, discharge.
rmg.add_zeros("topographic__elevation", at="node") # topographic elevation (m)
rmg.add_zeros("surface_water__depth", at="node") # water depth (m)
rmg.add_zeros("surface_water__discharge", at="link") # unit discharge (m2/s)
# Add our initial thin layer of water to the field of water depth.
# rmg['node']['surface_water__depth'] += h_init
# Now we'll identify our leftmost, but interior, column and the IDs of those
# nodes. One column in to prevent issues with BC.
inside_left_edge = rmg.nodes[1:-1, 1]
# Initializing our class...
of = OverlandFlow(rmg, mannings_n=n, theta=0.8, h_init=0.001)
# Now, we need to set a fixed value on the left edge, so we find the
# link neighbor arrays...
of.set_up_neighbor_arrays()
# ... and get a list of all horizonal ids, not just active ids (which is what
# the deAlmeida solution uses)
all_horizontal_ids = links.horizontal_link_ids(rmg.shape)
# from there, we are going to reset our west neighbor array...
of.west_neighbors = links.horizontal_west_link_neighbor(rmg.shape, all_horizontal_ids)
# and find the ids of the arrays along the west edge of the grid. We actually
# will set the discharge values here at every time step in the loop.
left_inactive_ids = links.left_edge_horizontal_ids(rmg.shape)
# DEM, depth, and discharge assignment
rmg['node']['topographic__elevation'] = z
rmg.add_zeros('node', 'surface_water__depth')
rmg.add_zeros('node', 'surface_water__discharge')
# Assign the outlet and boundary conditions
print("\tSetting Boundary Conditions...")
# If more than one outlet, errors out and show which outlets
# outlet_id = rmg.set_watershed_boundary_condition(z.flatten(), nodata_value=-9999, return_outlet_id=True)
outlet_id = 2615
rmg.set_watershed_boundary_condition_outlet_id(outlet_id, z.flatten())
# Object for managing the simulation
of = OverlandFlow(rmg, mannings_n=0.03, steep_slopes=True)
# Flow Routing
print("\tProcessing DEM for routing...")
sf = SinkFiller(rmg, routing='D4', apply_slope=False, fill_slope=1.e-5)
print("\tFilling pits...")
#sf.fill_pits()
print("\tOutputting topo from Landlab...")
write_netcdf('ll_topo.nc', rmg, names=['topographic__elevation'])
################################# FLOW SIM #####################################
# Show the user whats going on with the progress
print()
## Setting initial fields...
rmg['node']['topographic__elevation'] = z
rmg['link']['surface_water__discharge'] = np.zeros(rmg.number_of_links)
rmg['node']['surface_water__depth'] = np.zeros(rmg.number_of_nodes)
## and fixed link boundary conditions...
rmg.set_fixed_link_boundaries_at_grid_edges(True, True, True, True,
fixed_link_value_of='surface_water__discharge')
## Setting the outlet node to OPEN_BOUNDARY
rmg.status_at_node[100] = 1
## Initialize the OverlandFlow() class.
of = OverlandFlow(rmg, use_fixed_links = True, steep_slopes=True)
## Record the start time so we know how long it runs.
start_time = time.time()
## Link to sample at the outlet
link_to_sample = 299
## Storm duration in seconds
storm_duration = 7200.0
## Running the overland flow component.
while elapsed_time < model_run_time:
def reset(self):
"""
Reset function. Resets the world to its initial state.
"""
super(FloodWorld, self).reset()
# Terrain generation
shape = (self.grid_size,) * 2
size = self.grid_size * self.grid_size
# Set initial simple topography
z = self.vertical_scale * self.simple_topography(shape)
# Create raster model if it does not exist
if self.mg is None:
self.mg = RasterModelGrid(shape, int(round(self.world_size/self.grid_size)))
self.mg.set_closed_boundaries_at_grid_edges(True, True, True, True)
self.z = self.mg.add_field('node', 'topographic__elevation', z)
self.swd = self.mg.add_zeros('node', 'surface_water__depth')
else:
self.mg.at_node['topographic__elevation'] = z
self.swd[:] = np.zeros(size)
import matplotlib.pyplot as plt
plt.figure()
from landlab.plot import imshow_grid
imshow_grid(self.mg, 'topographic__elevation',
colorbar_label='m')
plt.draw()
# Set evolution parameters
uplift_rate = self.inputs['uplift_rate']
total_t = self.inputs['total_time']
dt = self.inputs['dt']
nt = int(total_t // dt) # Loops
uplift_per_step = uplift_rate * dt
self.fr = FlowAccumulator(self.mg, **self.inputs)
self.sp = FastscapeEroder(self.mg, **self.inputs)
# Erode terrain
for i in range(nt):
self.fr.run_one_step() # Not time sensitive
self.sp.run_one_step(dt)
self.mg.at_node['topographic__elevation'][self.mg.core_nodes] += uplift_per_step # add the uplift
if i % 10 == 0:
print('Erode: Completed loop %d' % i)
plt.figure()
imshow_grid(self.mg, 'topographic__elevation',
colorbar_label='m')
plt.draw()
plt.show()
# Setup surface water flow
self.of = OverlandFlow(self.mg, steep_slopes=True, mannings_n=0.01)
# Setup initial flood
self.swd[[5050, 5051, 5150, 5151]] += self.h_init
self.active = np.greater(np.flip(np.reshape(self.swd, shape), axis=0), self.flood_threshold)
class FloodWorld(ActiveCellWorld):
"""
FloodWorld class. This ActiveCellWorld implementation uses Landlab to simulate floods.
:param world_size:
:param grid_size:
:param torus:
:param agent_dynamic:
"""
def __init__(self, world_size, grid_size, torus, agent_dynamic):
super(FloodWorld, self).__init__(world_size, grid_size, torus, agent_dynamic)
# World generation parameters
self.vertical_scale = 200 # (m)
self.inputs = {'nrows': 100, 'ncols': 100, 'dx': 0.02, 'dt': 0.5, 'total_time': 50.0, 'uplift_rate': 0.001,
'K_sp': 0.3, 'm_sp': 0.5, 'n_sp': 1.0, 'rock_density': 2.7, 'sed_density': 2.7,
'linear_diffusivity': 0.0001}
# Flood parameters
self.h_init = 5 # initial thin layer of water (m)
self.n = 0.01 # roughness coefficient, (s/m^(1/3))
self.alpha = 0.7 # time-step factor (nondimensional; from Bates et al., 2010)
self.u = 0.4 # constant velocity (m/s, de Almeida et al., 2012)
self.cell_update_period = 10 # (s)
self.mg = None
self.fr = None
self.sp = None
self.of = None
self.swd = None
self.z = None
self.flood_threshold = 0.05 # minimum water depth detected as flood (m)
def reset(self):
"""
Reset function. Resets the world to its initial state.
"""
super(FloodWorld, self).reset()
# Terrain generation
shape = (self.grid_size,) * 2
size = self.grid_size * self.grid_size
# Set initial simple topography
z = self.vertical_scale * self.simple_topography(shape)
# Create raster model if it does not exist
if self.mg is None:
self.mg = RasterModelGrid(shape, int(round(self.world_size/self.grid_size)))
self.mg.set_closed_boundaries_at_grid_edges(True, True, True, True)
self.z = self.mg.add_field('node', 'topographic__elevation', z)
self.swd = self.mg.add_zeros('node', 'surface_water__depth')
else:
self.mg.at_node['topographic__elevation'] = z
self.swd[:] = np.zeros(size)
import matplotlib.pyplot as plt
plt.figure()
from landlab.plot import imshow_grid
imshow_grid(self.mg, 'topographic__elevation',
colorbar_label='m')
plt.draw()
# Set evolution parameters
uplift_rate = self.inputs['uplift_rate']
total_t = self.inputs['total_time']
dt = self.inputs['dt']
nt = int(total_t // dt) # Loops
uplift_per_step = uplift_rate * dt
self.fr = FlowAccumulator(self.mg, **self.inputs)
self.sp = FastscapeEroder(self.mg, **self.inputs)
# Erode terrain
for i in range(nt):
self.fr.run_one_step() # Not time sensitive
self.sp.run_one_step(dt)
self.mg.at_node['topographic__elevation'][self.mg.core_nodes] += uplift_per_step # add the uplift
if i % 10 == 0:
print('Erode: Completed loop %d' % i)
plt.figure()
imshow_grid(self.mg, 'topographic__elevation',
colorbar_label='m')
plt.draw()
plt.show()
# Setup surface water flow
self.of = OverlandFlow(self.mg, steep_slopes=True, mannings_n=0.01)
# Setup initial flood
self.swd[[5050, 5051, 5150, 5151]] += self.h_init
self.active = np.greater(np.flip(np.reshape(self.swd, shape), axis=0), self.flood_threshold)
def update_cells(self):
"""
Update cells function. Updates water level and cell status.
"""
self.of.overland_flow(dt=self.cell_update_period)
shape = (self.grid_size,) * 2
self.active = np.greater(np.flip(np.reshape(self.swd, shape), axis=0), self.flood_threshold)
@staticmethod
def noise_octave(shape, f):
"""
Noise octave function. Generates a noise map.
:param shape: (array) shape of the map.
:param f: (float) frequency bounds parameter.
"""
return te3w_util.fbm(shape, -1, lower=f, upper=(2 * f))
def simple_topography(self, shape):
"""
Simple topography function. Generates an elevation map.
:param shape: (array) shape of the map.
"""
values = np.zeros(shape)
for p in range(1, 10):
a = 2 ** p
values += np.abs(self.noise_octave(shape, a) - 0.5) / a
result = (1.0 - te3w_util.normalize(values)) ** 2
return result
